Information overloading occurs when a user is inundated with too much information about a topic of interest and when the desired information is obfuscated within multiple layers of abstraction. Yet, websites and applications are increasingly overloading their users because of the abundance and ease of acquiring and transmitting data over digital networks and because the additional information is often seen as a means with which one site provides differentiated or value added services relative to another site.
Search engine interaction provides one example of information overloading. When a user submits a search engine query, the search engine returns thousands, if not, millions of results that may be relevant to the user query. Already the user is overloaded with information. The user is not provided the sought after data in response to the search engine query. Rather, the user is given links to other sites. Thus, there is at least one layer of abstraction between the user and the desired data. In order for the user to obtain the desired data, the user has to select individual links to then retrieve a page or site that may or may not contain the sought after data. Yet, clicking on a link does not resolve the information overloading problem, and in many cases, can serve to exacerbate it. The presented page or site, may contain the sought after data, but it is more likely than not, that the page or site contains additional data, advertisements, graphics, media content, etc. that is extraneous or unrelated to the user query. In other words, the page or site is not customized for the visiting user. As a result, user sifts through the provided information in order to identify the data that is pertinent to the user. Thereafter, the user can begin to consume the data.
These same issues exist in the dissemination and consumption of objective and subjective business data. Objective business data is typically provided as financial reports and credit reports. These include several indicators, scores, and other data which convey sought after data in an information overloading manner. Similarly, subjective business data is also provided in an overloading manner. In most cases, review aggregation sites that provide subjective business data in the form of reviews and ratings mirror search engine operation. In response to a user query, a review aggregator site often presents a listing of businesses that match the user query, such that the user then has to select each business one-by-one in order to retrieve the subjective business data about that business and, when the subjective business data is presented, it is presented the same for all users with little to no per user customization. Thus, it is up to the user to sift through the presented data in order to identify the data that is sought after by the user.
More and more users are shifting from the “big” data paradigm to a “now” data paradigm, whereby users expect answers that are directly responsive to queries without intermediary layers of abstraction separating the user from the sought after data and without the inclusion of any extraneous or irrelevant data with the sought after data. If a user does not immediately receive the sought after data in an easily consumable means, then the user is likely to disengage and go elsewhere to obtain the data.
Accordingly, there is a need to provide objective and subjective business data in a manner that adheres to the “now” data paradigm. More specifically, there is a need to condense and format relevant business data and provide a presentation of that data that is customized for and directly responsive to the user. There is a need to remove any abstraction layers that separate the user from the sought after data. There is further a need to remove extraneous data that would have to be filtered by the user in order to arrive at and consume the sought after data.